Submission¶
Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace
In [1]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px
init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
| country | continent | year | lifeExp | pop | gdpPercap | iso_alpha | iso_num | |
|---|---|---|---|---|---|---|---|---|
| 0 | Afghanistan | Asia | 1952 | 28.801 | 8425333 | 779.445314 | AFG | 4 |
| 1 | Afghanistan | Asia | 1957 | 30.332 | 9240934 | 820.853030 | AFG | 4 |
| 2 | Afghanistan | Asia | 1962 | 31.997 | 10267083 | 853.100710 | AFG | 4 |
| 3 | Afghanistan | Asia | 1967 | 34.020 | 11537966 | 836.197138 | AFG | 4 |
| 4 | Afghanistan | Asia | 1972 | 36.088 | 13079460 | 739.981106 | AFG | 4 |
Question 1:¶
Recreate the barplot below that shows the population of different continents for the year 2007.
Hints:
- Extract the 2007 year data from the dataframe. You have to process the data accordingly
- use plotly bar
- Add different colors for different continents
- Sort the order of the continent for the visualisation. Use axis layout setting
- Add text to each bar that represents the population
In [3]:
# YOUR CODE HERE
df_2007 = df.query("year==2007")
# Group by continent and sum the population
df_2007_grouped = df_2007.groupby('continent', as_index=False).agg({'pop': 'sum'})
# Sort by population
df_2007_grouped = df_2007_grouped.sort_values(by='pop', ascending=False)
fig = px.bar(df_2007_grouped, y='continent', x='pop', color='continent', text='pop')
fig.update_layout(
title='Population of Different Continents in 2007',
xaxis_title='Continent',
yaxis_title='Population',
xaxis=dict(categoryorder='total descending'),
)
fig.show()
In [4]:
# YOUR CODE HERE
# The requirements for Q2 and Q3 are all completed in the Q1 code, so codes in Q2 and Q3 are the same with the codes in Q1.
fig = px.bar(df_2007_grouped, y='continent', x='pop', color='continent', text='pop')
fig.update_layout(
title='Population of Different Continents in 2007',
xaxis_title='Continent',
yaxis_title='Population',
xaxis=dict(categoryorder='total descending'),
)
fig.show()
Question 3:¶
Add text to each bar that represents the population
In [5]:
# YOUR CODE HERE
# The requirements for Q2 and Q3 are all completed in the Q1 code, so codes in Q2 and Q3 are the same with the codes in Q1.
fig = px.bar(df_2007_grouped, y='continent', x='pop', color='continent', text='pop')
fig.update_layout(
title='Population of Different Continents in 2007',
xaxis_title='Continent',
yaxis_title='Population',
xaxis=dict(categoryorder='total descending'),
)
fig.show()
Question 4:¶
Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years
In [11]:
# YOUR CODE HERE
df_grouped = df.groupby(['year', 'continent'], as_index=False).agg({'pop': 'sum'})
fig = px.bar(df_grouped,
y='continent',
x='pop',
color='continent',
animation_frame='year',
animation_group='continent',
title='Population Growth of Continents Over the Years',
labels={'pop': 'Population', 'continent': 'Continent'},
text='pop',
orientation='h')
fig.update_layout(
xaxis_title='Continent',
yaxis_title='Population',
xaxis=dict(range=[0, df_grouped['pop'].max()]),
yaxis=dict(categoryorder='total ascending'),
showlegend=False
)
fig.show()
Question 5:¶
Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years
In [16]:
# YOUR CODE HERE
df_grouped = df.groupby(['year', 'country'], as_index=False).agg({'pop': 'sum'})
fig = px.bar(df_grouped,
y='country',
x='pop',
color='country',
animation_frame='year',
animation_group='country',
title='Population Growth of Countries Over the Years',
labels={'pop': 'Population', 'country': 'Country'},
# text='pop' # delete text because texts are too small to work in normal animation.
)
fig.update_layout(
xaxis_title='Continent',
yaxis_title='Population',
xaxis=dict(range=[0, df_grouped['pop'].max()]),
yaxis=dict(categoryorder='total ascending'),
showlegend=False
)
fig.show()
Question 6:¶
Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation
In [18]:
# YOUR CODE HERE
df_grouped = df.groupby(['year', 'country'], as_index=False).agg({'pop': 'sum'})
fig = px.bar(df_grouped,
y='country',
x='pop',
color='country',
animation_frame='year',
animation_group='country',
title='Population Growth of Countries Over the Years',
labels={'pop': 'Population', 'country': 'Country'},
# text='pop' # delete text because texts are too small to work in normal animation.
)
fig.update_layout(
xaxis_title='Country',
yaxis_title='Population',
xaxis=dict(range=[0, df_grouped['pop'].max()]),
yaxis=dict(categoryorder='total ascending'),
showlegend=False,
height=1000 # Set the height size of the figure to 1000 to have a better view of the animation
)
fig.show()
In [20]:
# YOUR CODE HERE
# Group the top 10 countries
df_grouped['rank'] = df_grouped.groupby('year')['pop'].rank(method='first', ascending=False)
df_top10 = df_grouped[df_grouped['rank'] <= 10]
fig = px.bar(df_top10,
y='country',
x='pop',
color='country',
animation_frame='year',
animation_group='country',
title='Top 10 Most Populated Countries Over the Years',
labels={'pop': 'Population', 'country': 'Country'},
text='pop'
)
fig.update_layout(
xaxis_title='Country',
yaxis_title='Population',
xaxis=dict(range=[0, df_top10['pop'].max()]),
yaxis=dict(categoryorder='total ascending'),
showlegend=False,
height=1000
)
fig.show()